#198 Building Sophistication Into ML Ops Starts With The Strategic Vision, with Mia O’Dell, the GM of Data Science at Sportsbet

#198 Building Sophistication Into ML Ops Starts With The Strategic Vision, with Mia O’Dell, the GM of Data Science at Sportsbet

Author: Felipe Flores July 20, 2022 Duration: 38:42

Online wagering is one of the most sophisticated and complex fields for data and analytics. This week on the Data Futurology podcast, Mia O’Dell, the GM of Data Science at Sportsbet, kicks thing off by explaining how the company brings together three separate data teams, across three lines of business, to achieve meaningful and collaborative data outcomes.

Sportsbet is also growing its data practice and looking to nearly double its team sizes by the end of the year. O’Dell – who was also responsible for scaling the data practice in a previous organisation – also shares some insights about how to approach data scaling. There’s no “one size fits all” approach, she says. Success depends on being able to work with the teams to come up with a strong and compelling vision.

Finally, O’Dell also shares her concept of “machine learning offense” and “machine learning defence” as a way to help articulate the value of ML Ops at a time where non-data executives within enterprises are still struggling to understand the breakdown and operation of ML Ops teams.

It’s also important to understand where and when ML Ops becomes important to a business, O’Dell adds, saying that a lot of organisations make the mistake of going all-out when they’re just at the start of the journey, where the value of ML Ops will be marginal and difficult to articulate.

“If your first machine learning model is something that’s extremely critical to the success of the business, of course you want to over invest in its reliance,” she says. “But for something that isn’t necessarily core to the business, ML Ops can result in putting far too much effort on the defensive side, and not enough yet on the offensive side.”

Tune in for in-depth insights into this, and more, with Mia O’Dell.

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In a field dominated by discussions of algorithms and infrastructure, Data Futurology carves out a different, crucial space. Host Felipe Flores guides conversations toward the human-centric challenges that ultimately determine whether an AI initiative succeeds or fails. This isn't a technical deep dive into model architectures; it's a series of dialogues about strategy, organizational change, and the practical leadership required to bridge the gap between potential and real-world impact. You'll hear from practitioners and executives who have navigated the complex last mile of deployment, where the real work of integrating technology into business processes and culture happens. The podcast explores how to select the right problems, build effective teams, and cultivate an ethical, forward-thinking approach to data science and machine learning. For leaders, managers, and anyone responsible for steering their organization through the adoption of these powerful tools, Data Futurology offers grounded insights and actionable perspectives. It’s about moving beyond the hype to create sustainable value, ensuring that the rapid pace of advancement in artificial intelligence is matched by thoughtful and effective human leadership. Tune in for a necessary complement to the more code-focused shows in your feed.
Author: Language: English Episodes: 100

Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science
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